An important component of a controlled motor-drive system is an electro-mechanical machine. Depending on the application, such machines can be used either as a generator or a motor through the interaction of their “stator magnetic field” and their “rotor magnetic field”, to convert mechanical energy to electrical energy, or vice versa, as is well known in the field of controlled motor-drive systems. Generally at least four distinct types of machines can be identified, based on how the stator and rotor magnetic fields are produced and interacted with each other. These types include a Permanent Magnet Synchronous Machine (PMSM), wherein a rotating magnetic field is generated by the application of a three phase balanced AC voltage to the stator. Permanent magnets may be used in the rotor, to establish the rotor magnetic field. Another further type includes a Brushless DC Machine (BLDC), similar to the PMSM, except that instead of exciting all the three stator windings, only two windings of the stator windings may be excited at the same time, which results in trapezoidal as opposed to sinusoidal currents for windings. Another further type includes a Wound-Rotor Synchronous Machine (WRSM), wherein a rotating magnetic field is generated by the application of a three-phase balanced AC voltage to the stator, similar to the PMSM. Though for the WRSM, the rotor magnetic filed may be produced by passing a DC current in a distributed winding in the rotor. This current can be transferred to the rotor field winding through “slip-rings and brushes”, or through a brushless method. And another further type includes an Induction Machine (IM), wherein the stator may be excited in the same way as the PMSM, but the rotor magnetic field is established by induction from the stator field at a different frequency as compared to the stator, and is thus called an asynchronous machine.
For these types of motor drive systems described above, a commonly utilized control system, used in aerospace and industrial applications, includes a closed-loop arrangement to measure the speed and/or position of a motor (e.g., permanent magnet synchronous motor—PMSM), particularly the PMSM rotor speed and/or position. FIG. 1 illustrates a prior art closed-loop control system 100 for measuring the rotor speed/position of a PMSM 106. The closed-loop system 100 includes DC power supply 102, inverter 104 which is powered by supply 102, pulse width modulating signal (PWMS) generator 110, shaft sensor 108, speed controller 116, frame transformation devices 112, 114. During conventional operation, the system 100 uses speed controller 116 to generate a current reference 122 from the difference between a speed reference 117 and the measured speed 120 output from sensor 108 (e.g., hall sensor). Two projected components (I*d and I*q), on d and q axes, respectively, of the reference current 122 are compared to dq components, output from frame transformer 114, of measured three phase components (Ia, Ib, Ic) from inverter 104. The measured error between the dq components and the projected components produces the control variables Vd and Vq which are input to frame transformer 112, along with the measured rotor position 121 output from sensor 108, to produce dq-to-abc components Va, Vb, Vc which are three-phase voltage reference values. These references values are input to PWM generator 110 to produce PWM signals for inverter 104 to produce output voltages from the three-phase inverter 104 to drive PMSM 106.
This technique shown in FIG. 1, however, increases system complexity and decreases system reliability. The PMSM 106 must have the sensor 108 built in or attached mechanically to the rotor, and interfaces and wiring must be added for control (excitation) and feedback signals (e.g., Va, Vb, Vc, Ia, Ib, Ic) between the controller 116 and the sensor 108. Also, PMSM 106 may be located at a distance from controller 116 creating the need for unwanted extra wiring in the system.
To avoid the wiring and other disadvantages of a sensor control system, sensorless motor control techniques may be used to increase system reliability and eliminate the need for extra wiring in the system. In addition, these techniques eliminate the need for a discrete position sensor and also reduce the system cost. A sensorless motor control technique may be a more flexible/adaptable solution for a motor drive system than one that relies on a separate position sensor. It may be particularly valuable for an aircraft system where increased reliability and reduction of weight (e.g., through elimination of the sensor and additional wiring) are extremely important.
For linear systems, a Kalman filter may be used to determine the states and outputs of a system as shown in FIG. 19 which shows the structure of a Kalman filter 1900. For filter 1900, we may assume a system with the following equations:{dot over (x)}=A·x+B·u+σ,  (1)y=H·x+ρ.  (2)where σ and ρ are the system and the measurement noises, which are stationary, white, uncorrelated and Gauss noises, and the expectations are zeros. Further, the covariance matrices of these noises may be defined as:Q=E[σ·σT],  (3)R=E[ρ·ρT].  (4)where E[ ] denotes expected values.The system equation of Kalman filter 1900 becomes:{circumflex over ({dot over (x)}=(A−K·H)·{circumflex over (x)}+B·u+K·y  (5).Matrix K may be set based on the covariance of the noises. A measure of the goodness of the observation may be established as:J=E[eT·e].  (6)where e follows:e=x−{circumflex over (x)}.  (7).Advantageously, K may be chosen to make J minimal where the solution is the followingK=P·HT·R−1.  (8)where P can be calculated from the solution of the following Riccati equation:P·HT·R−1·H·P−A·P−P·AT−Q=0.  (9)Q and R may be set up based on the stochastic properties of the corresponding noises.
However, the Kalman filter 1900 is only useful for linear systems which necessitates the generation of an Extended Kalman Filter (estimator) as described herein particularly suited for non-linear systems which may be encountered for motor-drive systems.
A conventional sensorless control system may be used to measure PMSM rotor speed and/or position (a non-linear system) as illustrated by prior art control system 200 shown in FIG. 2. Control system 200 includes similar components from system 100 in FIG. 1 except that speed and position outputs 203, 205 are estimated by speed and position estimator 109 instead of measured by sensor 108. As shown in FIG. 2, estimator 109 receives as input three-phase current components Ia, Ib, Ic generated by inverter 104 and receives as input three-phase voltage components Va, Vb, Vc voltages from frame transformer 1112. Estimator 109 may use a two current loop system to correct for an initial, estimated rotor position, and to correct and update flux-linkage produced in the PMSM which generates sufficient torque in the system 200 such that PMSM may be used as a starter and/or generator. Also, estimator may estimate the motor line current from the input current components, calculate the error between the current estimate and the measured current, and use the error calculation to determine the speed and position of the rotor for a particular time interval. Subsequently, the process may be repeated for future time intervals to correct flux-linkage and predict rotor position. Advantageously, this process may be used for both brushless DC motors (BLDCM) and PMSMs, but control system performance may degrade based on the quality and accuracy of flux-linkage estimates and measurements of system voltages and currents. Additionally, control system accuracy may degrade from system harmonics and noise, machine parameter variations due to temperature changes and magnetic saturation.
Other prior art sensorless methods utilize a state observer technique but these methods are susceptible to motor drive system parameter variation and require complex non-linear control theory, which make these other methods difficult to fine-tune and implement. Such methods also suffer from additional limitations including lack of any accurate information on the initial rotor position which is further complicated by initial speed/position convergence problems, and the need for injecting a current pulse at the start-up of the motor to avoid a stall condition. Lack of proper operation of such methods has prevented their accuracy and effectiveness over the full speed and torque range, required by dynamic loads, which is a main reason for sensorless control of drive systems not becoming wide-spread.
Therefore, due to the disadvantages of current sensorless control systems for motor-drive systems, there is a need to provide a state observer control method that overcomes these limitations and provides a robust, easily implemented, sensorless control apparatus for a motor-drive system.